Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

The nonlinear impact of industrial restructuring on economic growth and carbon dioxide emissions: a panel threshold regression approach

  • 17 Accesses


Energy conservation, emission reduction, and sustainable development are the goals of achieving low-carbon economic development all over the world. Many countries are working hard to find measures, and industrial restructuring is considered to be an effective way to achieve economic development and emission reduction. However, previous studies have assumed that industrial restructuring and economic growth and emissions are simple linear relationships while neglecting nonlinear relationships. We use panel data from 32 countries from 1997 to 2017 and employ panel threshold models (Stochastic Impacts by Regression on Population, Affluence and Technology model and Solow growth model) for empirical test. The results reveal that industrial restructuring has statistically significant nonlinear effects on economic growth and carbon dioxide emissions. With the process of industrialization and urbanization, industrial restructuring has a long-term positive impact on economic growth. The relationship among industrial restructuring and carbon dioxide emissions has been found to be inverted U–shaped. Industrial restructuring is beneficial to reducing emissions. The policy implies that although industrial restructuring is considered to be an effective measure to achieve green growth, for countries with different degrees of urbanization and economic development, industrial structure transformation should adopt different policies.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4


  1. Baily MN, Bartelsman EJ, Haltiwanger J (2001) Labor productivity: structural change and cyclical dynamics. Rev Econ Stat 83:420–433. https://doi.org/10.1162/00346530152480072

  2. Berthélemy J-c, Söderling L (2001) The role of capital accumulation, adjustment and structural change for economic take-off: empirical evidence from African growth episodes. World Dev 29:323–343. https://doi.org/10.1016/S0305-750X(00)00095-4

  3. Botta A (2009) A structuralist north–south model on structural change, economic growth and catching-up. Struct Chang Econ Dyn 20:61–73. https://doi.org/10.1016/j.strueco.2008.12.001

  4. Breitung J (2001) The local power of some unit root tests for panel data. In: Advances in econometrics, vol 15. Emerald Group Publishing Limited, Bingley 161–177. https://doi.org/10.1016/S0731-9053(00)15006-6

  5. Brondino G (2019) Productivity growth and structural change in China (1995–2009): a subsystems analysis. Struct Chang Econ Dyn 49:183–191. https://doi.org/10.1016/j.strueco.2018.09.001

  6. Chang N (2015) Changing industrial structure to reduce carbon dioxide emissions: a Chinese application. J Clean Prod 103:40–48. https://doi.org/10.1016/j.jclepro.2014.03.003

  7. Chang N, Li Z (2017) Decoupling the lock-in effect between economic growth and CO2 emissions by structure adjustment: a final demand perspective. J Clean Prod 154:94–101. https://doi.org/10.1016/j.jclepro.2017.03.128

  8. Chen S, Jefferson GH, Zhang J (2011) Structural change, productivity growth and industrial transformation in China. China Econ Rev 22:133–150. https://doi.org/10.1016/j.chieco.2010.10.003

  9. Chen D, Chen S, Jin H (2018) Industrial agglomeration and CO2 emissions: evidence from 187 Chinese prefecture-level cities over 2005–2013. J Clean Prod 172:993–1003. https://doi.org/10.1016/j.jclepro.2017.10.068

  10. Chen S, Zhang Y, Zhang Y, Liu Z (2019) The relationship between industrial restructuring and China’s regional haze pollution: a spatial spillover perspective. J Clean Prod 239:115808. https://doi.org/10.1016/j.jclepro.2019.02.078

  11. Cherniwchan J (2012) Economic growth, industrialization, and the environment. Resour Energy Econ 34:442–467. https://doi.org/10.1016/j.reseneeco.2012.04.004

  12. Choi I (2001) Unit root tests for panel data. J Int Money Financ 20:249–272. https://doi.org/10.1016/S0261-5606(00)00048-6

  13. Cutrini E (2019) Economic integration, structural change, and uneven development in the European Union. Struct Chang Econ Dyn 50:102–113. https://doi.org/10.1016/j.strueco.2019.06.007

  14. Destek MA (2016) Renewable energy consumption and economic growth in newly industrialized countries: evidence from asymmetric causality test. Renew Energy 95:478–484. https://doi.org/10.1016/j.renene.2016.04.049

  15. Ehrlich PR, Holdren JP (1971) Impact of population growth. Science 171:1212–1217 https://www.jstor.org/stable/1731166

  16. Erumban AA, Das DK, Aggarwal S, Das PC (2019) Structural change and economic growth in India. Struct Chang Econ Dyn 51:186–202. https://doi.org/10.1016/j.strueco.2019.07.006

  17. Fagerberg J (2000) Technological progress, structural change and productivity growth: a comparative study. Struct Chang Econ Dyn 11:393–411. https://doi.org/10.1016/S0954-349X(00)00025-4

  18. Fan S, Zhang X, Robinson S (2003) Structural Change and Economic Growth in China. Rev Dev Econ 7:360–377. https://doi.org/10.1111/1467-9361.00196

  19. Feng Y, Zhong S, Li Q, Zhao X, Dong X (2019) Ecological well-being performance growth in China (1994–2014): from perspectives of industrial structure green adjustment and green total factor productivity. J Clean Prod 236:117556. https://doi.org/10.1016/j.jclepro.2019.07.031

  20. Gabriel LF, Jayme FG, Oreiro JL (2016) A north-south model of economic growth, technological gap, structural change and real exchange rate. Struct Chang Econ Dyn 38:83–94. https://doi.org/10.1016/j.strueco.2016.03.003

  21. Gu G, Wang Z (2018) China’s carbon emissions abatement under industrial restructuring by investment restriction. Struct Chang Econ Dyn 47:133–144. https://doi.org/10.1016/j.strueco.2018.08.007

  22. Hansen BE (1999) Threshold effects in non-dynamic panels: estimation, testing, and inference. J Econ 93:345–368. https://doi.org/10.1016/S0304-4076(99)00025-1

  23. Holland D, Cooke SC (1992) Sources of structural change in the Washington economy. Ann Reg Sci 26:155–170. https://doi.org/10.1007/BF02116367

  24. Im KS, Pesaran MH, Shin Y (2003) Testing for unit roots in heterogeneous panels. J Econ 115:53–74. https://doi.org/10.1016/S0304-4076(03)00092-7

  25. Jänicke M, Mönch H, Ranneberg T, Simonis UE (1989) Economic structure and environmental impacts: East-west comparisons. Environmentalist 9:171–183. https://doi.org/10.1007/BF02240467

  26. Kabiraj T, Chyi Lee C (2004) Synergy, learning and the changing industrial structure. Int Econ J 18:365–387. https://doi.org/10.1080/1016873042000270018

  27. Kao C (1999) Spurious regression and residual-based tests for cointegration in panel data. J Econ 90:1–44. https://doi.org/10.1016/S0304-4076(98)00023-2

  28. Kofi Adom P, Bekoe W, Amuakwa-Mensah F, Mensah JT, Botchway E (2012) Carbon dioxide emissions, economic growth, industrial structure, and technical efficiency: empirical evidence from Ghana, Senegal, and Morocco on the causal dynamics. Energy 47:314–325. https://doi.org/10.1016/j.energy.2012.09.025

  29. Larsson R, Lyhagen J, Löthgren M (2001) Likelihood-based cointegration tests in heterogeneous panels. Econ J 4:109–142. https://doi.org/10.1111/1368-423x.00059

  30. Levin A, Lin C-F, James Chu C-S (2002) Unit root tests in panel data: asymptotic and finite-sample properties. J Econ 108:1–24. https://doi.org/10.1016/S0304-4076(01)00098-7

  31. Li K, Lin B (2017) Economic growth model, structural transformation, and green productivity in China. Appl Energy 187:489–500. https://doi.org/10.1016/j.apenergy.2016.11.075

  32. Li Z et al (2017) Examining industrial structure changes and corresponding carbon emission reduction effect by combining input-output analysis and social network analysis: a comparison study of China and Japan. J Clean Prod 162:61–70. https://doi.org/10.1016/j.jclepro.2017.05.200

  33. Li JS, Zhou HW, Meng J, Yang Q, Chen B, Zhang YY (2018a) Carbon emissions and their drivers for a typical urban economy from multiple perspectives: a case analysis for Beijing City. Appl Energy 226:1076–1086. https://doi.org/10.1016/j.apenergy.2018.06.004

  34. Li L, Lei Y, Wu S, He C, Chen J, Yan D (2018b) Impacts of city size change and industrial structure change on CO2 emissions in Chinese cities. J Clean Prod 195:831–838. https://doi.org/10.1016/j.jclepro.2018.05.208

  35. Li Z, Shao S, Shi X, Sun Y, Zhang X (2019) Structural transformation of manufacturing, natural resource dependence, and carbon emissions reduction: evidence of a threshold effect from China. J Clean Prod 206:920–927. https://doi.org/10.1016/j.jclepro.2018.09.241

  36. Lin JY, Xu JT (2014) The potential for green growth and structural transformation in China. Oxf Rev Econ Policy 30:550–568. https://doi.org/10.1093/oxrep/gru030

  37. Lin B, Omoju OE, Okonkwo JU (2015) Impact of industrialisation on CO2 emissions in Nigeria. Renew Sust Energ Rev 52:1228–1239. https://doi.org/10.1016/j.rser.2015.07.164

  38. Liu X, Bae J (2018) Urbanization and industrialization impact of CO2 emissions in China. J Clean Prod 172:178–186. https://doi.org/10.1016/j.jclepro.2017.10.156

  39. Llop M (2007) Economic structure and pollution intensity within the environmental input–output framework. Energy Policy 35:3410–3417. https://doi.org/10.1016/j.enpol.2006.12.015

  40. Mao G et al (2013) Reducing carbon emissions in China: industrial structural upgrade based on system dynamics. Energy Strateg Rev 2:199–204. https://doi.org/10.1016/j.esr.2013.07.004

  41. McCoskey S, Kao C (1997) A residual-based test of the null of cointegration in panel data. Econ Rev 17:57–84. https://doi.org/10.1080/07474939808800403

  42. McGillivray M (2003) Policy-based lending, structural adjustment and economic growth in Pakistan. J Policy Model 25:113–121. https://doi.org/10.1016/S0161-8938(02)00207-7

  43. Mi Z-F, Pan S-Y, Yu H, Wei Y-M (2015) Potential impacts of industrial structure on energy consumption and CO2 emission: a case study of Beijing. J Clean Prod 103:455–462. https://doi.org/10.1016/j.jclepro.2014.06.011

  44. Minihan ES, Wu Z (2012) Economic structure and strategies for greenhouse gas mitigation. Energy Econ 34:350–357. https://doi.org/10.1016/j.eneco.2011.05.011

  45. Montobbio F (2002) An evolutionary model of industrial growth and structural change. Struct Chang Econ Dyn 13:387–414. https://doi.org/10.1016/S0954-349X(02)00006-1

  46. Mudakkar SR, Zaman K, Khan MM, Ahmad M (2013) Energy for economic growth, industrialization, environment and natural resources: living with just enough. Renew Sust Energ Rev 25:580–595. https://doi.org/10.1016/j.rser.2013.05.024

  47. Pedroni P (2004) Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Economic Theory 20:597–625. https://doi.org/10.1017/S0266466604203073

  48. Peneder M (2003) Industrial structure and aggregate growth. Struct Chang Econ Dyn 14:427–448. https://doi.org/10.1016/S0954-349X(02)00052-8

  49. Rauf A, Zhang J, Li J, Amin W (2018) Structural changes, energy consumption and carbon emissions in China: empirical evidence from ARDL bound testing model. Struct Chang Econ Dyn 47:194–206. https://doi.org/10.1016/j.strueco.2018.08.010

  50. Rekiso ZS (2017) Rethinking regional economic integration in Africa as if industrialization mattered. Struct Chang Econ Dyn 43:87–98. https://doi.org/10.1016/j.strueco.2017.10.001

  51. Salahuddin M, Alam K, Ozturk I (2016) The effects of Internet usage and economic growth on CO2 emissions in OECD countries: a panel investigation. Renew Sust Energ Rev 62:1226–1235. https://doi.org/10.1016/j.rser.2016.04.018

  52. Samouilidis JE, Mitropoulos CS (1984) Energy and economic growth in industrializing countries: the case of Greece. Energy Econ 6:191–201. https://doi.org/10.1016/0140-9883(84)90016-1

  53. Shahbaz M, Nasreen S, Ahmed K, Hammoudeh S (2017) Trade openness–carbon emissions nexus: the importance of turning points of trade openness for country panels. Energy Econ 61:221–232. https://doi.org/10.1016/j.eneco.2016.11.008

  54. Sharif Hossain M (2011) Panel estimation for CO2 emissions, energy consumption, economic growth, trade openness and urbanization of newly industrialized countries. Energy Policy 39:6991–6999. https://doi.org/10.1016/j.enpol.2011.07.042

  55. Solow RM (1956) A contribution to the theory of economic growth. Q J Econ 70:65–94. https://doi.org/10.2307/1884513

  56. Song J, Yang W, Higano Y, Xe W (2015) Introducing renewable energy and industrial restructuring to reduce GHG emission: application of a dynamic simulation model. Energy Convers Manag 96:625–636. https://doi.org/10.1016/j.enconman.2015.03.024

  57. Szirmai A (2012) Industrialisation as an engine of growth in developing countries, 1950–2005. Struct Chang Econ Dyn 23:406–420. https://doi.org/10.1016/j.strueco.2011.01.005

  58. Teixeira AAC, Queirós ASS (2016) Economic growth, human capital and structural change: a dynamic panel data analysis. Res Policy 45:1636–1648. https://doi.org/10.1016/j.respol.2016.04.006

  59. Tian X, Chang M, Shi F, Tanikawa H (2014) How does industrial structure change impact carbon dioxide emissions? A comparative analysis focusing on nine provincial regions in China. Environ Sci Pol 37:243–254. https://doi.org/10.1016/j.envsci.2013.10.001

  60. Vu KM (2017) Structural change and economic growth: empirical evidence and policy insights from Asian economies. Struct Chang Econ Dyn 41:64–77. https://doi.org/10.1016/j.strueco.2017.04.002

  61. Wang K, Wu M, Sun Y, Shi X, Sun A, Zhang P (2019a) Resource abundance, industrial structure, and regional carbon emissions efficiency in China. Resour Policy 60:203–214. https://doi.org/10.1016/j.resourpol.2019.01.001

  62. Wang Q, Su M, Li R, Ponce P (2019b) The effects of energy prices, urbanization and economic growth on energy consumption per capita in 186 countries. J Clean Prod 225:1017–1032. https://doi.org/10.1016/j.jclepro.2019.04.008

  63. Westerlund J (2005) A panel CUSUM test of the null of cointegration. Oxf Bull Econ Stat 67:231–262. https://doi.org/10.1111/j.1468-0084.2004.00118.x

  64. Wu R, Dai H, Geng Y, Xie Y, Tian X (2019) Impacts of export restructuring on national economy and CO2 emissions: a general equilibrium analysis for China. Appl Energy 248:64–78. https://doi.org/10.1016/j.apenergy.2019.04.024

  65. Xu B, Lin B (2015) How industrialization and urbanization process impacts on CO2 emissions in China: evidence from nonparametric additive regression models. Energy Econ 48:188–202. https://doi.org/10.1016/j.eneco.2015.01.005

  66. Xu B, Lin B (2017) Assessing CO2 emissions in China’s iron and steel industry: a nonparametric additive regression approach. Renew Sust Energ Rev 72:325–337. https://doi.org/10.1016/j.rser.2017.01.009

  67. York R, Rosa EA, Dietz T (2003) STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts. Ecol Econ 46:351–365. https://doi.org/10.1016/S0921-8009(03)00188-5

  68. Zhang M, Huang X-J (2012) Effects of industrial restructuring on carbon reduction: an analysis of Jiangsu Province, China. Energy 44:515–526. https://doi.org/10.1016/j.energy.2012.05.050

  69. Zhang J, Jiang H, Liu G, Zeng W (2018a) A study on the contribution of industrial restructuring to reduction of carbon emissions in China during the five Five-Year Plan periods. J Clean Prod 176:629–635. https://doi.org/10.1016/j.jclepro.2017.12.133

  70. Zhang P, Yuan H, Bai F, Tian X, Shi F (2018b) How do carbon dioxide emissions respond to industrial structural transitions? Empirical results from the northeastern provinces of China. Struct Chang Econ Dyn 47:145–154. https://doi.org/10.1016/j.strueco.2018.08.005

  71. Zhang S, Li H, Zhang Q, Tian X, Shi F (2019) Uncovering the impacts of industrial transformation on low-carbon development in the Yangtze River Delta. Resour Conserv Recycl 150:104442. https://doi.org/10.1016/j.resconrec.2019.104442

  72. Zhou A, Li J (2019) Heterogeneous role of renewable energy consumption in economic growth and emissions reduction: evidence from a panel quantile regression. Environ Sci Pollut Res 26:22575–22595. https://doi.org/10.1007/s11356-019-05447-w

  73. Zhou X, Zhang J, Li J (2013) Industrial structural transformation and carbon dioxide emissions in China. Energy Policy 57:43–51. https://doi.org/10.1016/j.enpol.2012.07.017

  74. Zhu Y, Shi Y, Wang Z (2014) How much CO2 emissions will be reduced through industrial structure change if China focuses on domestic rather than international welfare? Energy 72:168–179. https://doi.org/10.1016/j.energy.2014.05.022

  75. Zhu Z, Liu Y, Tian X, Wang Y, Zhang Y (2017) CO2 emissions from the industrialization and urbanization processes in the manufacturing center Tianjin in China. J Clean Prod 168:867–875. https://doi.org/10.1016/j.jclepro.2017.08.245

  76. Zhu B et al (2019) Exploring the effect of industrial structure adjustment on interprovincial green development efficiency in China: a novel integrated approach. Energy Policy 134:110946. https://doi.org/10.1016/j.enpol.2019.110946

Download references


The authors thank the anonymous reviewers for their valuable suggestions for this article.


This paper was funded by the Hunan Provincial Natural Science Foundation (No. 2018JJ2264).

Author information

Correspondence to Jun Li.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


1. The impact of industrial restructuring on economic growth and emissions is investigated.

2. Both linear and nonlinear panel analyses are conducted.

3. Industrial restructuring has a positive impact on economic growth and emission reduction.

4. There is an inverted U–shaped relationship between industrial restructuring and carbon emissions

5. Economic growth and urbanization promote emission reduction effect of industrial restructuring.

Responsible editor: Nicholas Apergis

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhou, A., Li, J. The nonlinear impact of industrial restructuring on economic growth and carbon dioxide emissions: a panel threshold regression approach. Environ Sci Pollut Res (2020). https://doi.org/10.1007/s11356-020-07778-5

Download citation


  • Industrial restructuring
  • Economic growth
  • Emission reduction
  • Panel threshold regression